Senior Data Analyst

DGH Recruitment Ltd
City of London
1 month ago
Applications closed

Related Jobs

View all jobs

Senior Data Analyst

Senior Data Analyst

Senior Data Analyst

Senior Data Analyst

Senior Data Analyst

Senior Data Analyst

Senior Data Analyst

An exciting opportunity has arisen for a Senior Data Analyst to join and will take the lead on shaping and delivering the company's data strategy, working closely with senior stakeholders across the business.

This position is ideal for someone who is both technically hands‑on and capable of driving strategic data initiatives, with a clear progression route into future leadership.

Responsibilities:

Lead the design and delivery of data solutions that support business growth.
Develop advanced dashboards and reporting, primarily using Power BI.
Own and manage data quality and data processes within Dynamics 365.
Build scalable data models, ETL pipelines, APIs and system integrations.
Manage the data team's ticketing workflow and ensure timely resolution of issues.
Translate requirements from technical and non‑technical stakeholders into actionable solutions.
Champion best practice in data governance, security, FCA compliance and GDPR.
Produce and maintain technical documentation including data dictionaries and maps.
Mentor junior team members and help shape the growing data function.

Required Experience & Skills

Strong background in data analytics or data engineering, ideally within regulated environments.
Advanced experience with Power BI and Dynamics 365.
Skilled in SQL, Python, API development and systems integration.
Experience building scalable data architectures and ETL processes.
Excellent communication skills with the ability to simplify complex concepts.
Proven project delivery across multiple workstreams.
Thorough understanding of data governance and security principles.
Experience mentoring others and a desire to progress into leadership.

In accordance with the Employment Agencies and Employment Businesses Regulations 2003, this position is advertised based upon DGH Recruitment Limited having first sought approval of its client to find candidates for this position.

DGH Recruitment Limited acts as both an Employment Agency and Employment Business

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

How Many Data Science Tools Do You Need to Know to Get a Data Science Job?

If you’re trying to break into data science — or progress your career — it can feel like you are drowning in names: Python, R, TensorFlow, PyTorch, SQL, Spark, AWS, Scikit-learn, Jupyter, Tableau, Power BI…the list just keeps going. With every job advert listing a different combination of tools, many applicants fall into a trap: they try to learn everything. The result? Long tool lists that sound impressive — but little depth to back them up. Here’s the straight-talk version most hiring managers won’t explicitly tell you: 👉 You don’t need to know every data science tool to get hired. 👉 You need to know the right ones — deeply — and know how to use them to solve real problems. Tools matter, but only in service of outcomes. So how many data science tools do you actually need to know to get a job? For most job seekers, the answer is not “27” — it’s more like 8–12, thoughtfully chosen and well understood. This guide explains what employers really value, which tools are core, which are role-specific, and how to focus your toolbox so your CV and interviews shine.

What Hiring Managers Look for First in Data Science Job Applications (UK Guide)

If you’re applying for data science roles in the UK, it’s crucial to understand what hiring managers focus on before they dive into your full CV. In competitive markets, recruiters and hiring managers often make their first decisions in the first 10–20 seconds of scanning an application — and in data science, there are specific signals they look for first. Data science isn’t just about coding or statistics — it’s about producing insights, shipping models, collaborating with teams, and solving real business problems. This guide helps you understand exactly what hiring managers look for first in data science applications — and how to structure your CV, portfolio and cover letter so you leap to the top of the shortlist.

The Skills Gap in Data Science Jobs: What Universities Aren’t Teaching

Data science has become one of the most visible and sought-after careers in the UK technology market. From financial services and retail to healthcare, media, government and sport, organisations increasingly rely on data scientists to extract insight, guide decisions and build predictive models. Universities have responded quickly. Degrees in data science, analytics and artificial intelligence have expanded rapidly, and many computer science courses now include data-focused pathways. And yet, despite the volume of graduates entering the market, employers across the UK consistently report the same problem: Many data science candidates are not job-ready. Vacancies remain open. Hiring processes drag on. Candidates with impressive academic backgrounds fail interviews or struggle once hired. The issue is not intelligence or effort. It is a persistent skills gap between university education and real-world data science roles. This article explores that gap in depth: what universities teach well, what they often miss, why the gap exists, what employers actually want, and how jobseekers can bridge the divide to build successful careers in data science.